Pregnancy presents a hematologic paradox. Despite hemorrhage being the leading cause of maternal mortality worldwide, pregnancy is a well described hypercoaguable state, conferring a significant increase in clinical thromboembolic events observed during pregnancy and the puerperium. This hypercoagulable state appears linked to increases in sex hormone levels. However, the vast majority of pregnant women (99.9%) do not have a thrombotic event during pregnancy or the post-partum period, although bleeding complications and preeclampsia (with its associated hematologic disorders) exist in approximately 10% of women. Additionally, in women undergoing pharmacologic ovulation induction the risk of thrombosis in the first trimester is increased up to 10-fold, but here too the vast majority (99.6%) maintain an appropriate hemostatic balance and remain free of clinical complications. In this proposal, we will identify compensating mechanisms that confer protection from thrombosis and build mathematical models that combine these mechanistic insights with an individual's specific clinical parameters and select biomarker values to predict risk for aberrant hemostasis across pregnancy. R61: Identify and quantitatively assess the hemostatic pathways in place that may protect against thrombotic events and how pharmacologic ovulation induction and peripartum events may affect these pathways. We will collect data to establish a natural history relevant to sex hormone influence during pregnancy. In one cohort, assisted and natural pregnancy will be longitudinally assessed from pre-pregnancy to the first trimester while in the other cohort, pregnancy will be followed from the 3rd trimester to several months postpartum comparing cesarean delivery with and without labor with vaginal delivery. Data will include clinical and anthropometric parameters, dynamic assessments of hemostatic balance (thrombus stability), biomarker measurements capturing alterations in pre-pregnancy coagulant/anticoagulant/fibrinolytic components and pathways, and markers of inflammation and cellular activation. Computational modeling assessing the contributions of the coagulant, anticoagulant and fibrinolytic proteome of each individual will provide mechanistic insights into observed alterations in hemostatic balance. R33: 1) Develop models that integrate clinical data, dynamic measures and biomarker data from the R61 phase to both identify mechanisms that confer protection from thrombosis and to predict individual risk for the most common clinical problems, including failure to implant during assisted pregnancy and hemorrhage during delivery; 2) Initiate a longitudinal study of assisted and natural pregnancy in which each individual is followed from pre-pregnancy into the postpartum period using dynamic and static assays (from R61 phase) that appeared most responsive to the changes in sex hormone concentrations; 3) Mature and validate the preliminary models using the longitudinal study data. ...